RE and ML have a special connection. We can see a machine-learned model as a specification based on training data since data is a learned description of how the model shall behave [1]}. Nevertheless, most ML models lack requirements specifications since current RE practices are not well defined and organized for ML [2]}[3]}. Assuring the quality of the specifications is crucial for project success since misunderstandings and defects in requirements documents can easily lead to design flaws and cause severe and costly problems. Good requirements should be, at a minimum, complete, consistent, correct, unambiguous and testable [4]}.
